geepack.lgst.int.batch.imputed: function to test gene-environment or gene-gene interactions...

In GWAF: Genome-Wide Association/Interaction Analysis and Rare Variant Analysis with Family Data

Description

Fit logistic regression via Generalized Estimation Equation (GEE) to test gene-environment or gene-gene interactions between a dichotomous phenotype and all imputed SNPs in a genotype file in family data under additive genetic model. The interaction term is the product of SNP genotype and a covariate for interaction (cov.int). The covariate for interaction (cov.int) can be SNP genotype (gene-gene interaction) or an environmental factor (gene-environment interaction). Only one interaction term is allowed. When cov.int is dichotomous, stratified analyses can be requested by specifying sub="Y". The covariance between the main effect (SNP) and the interaction effect is provided in the output when stratified analysis is not requested. Each family is treated as a cluster, with independence working correlation matrix used in the robust variance estimator. This function applies the same interaction test to all SNPs in the imputed genotype data. The interaction test is carried out by geepack.lgst.int.imputed function from GWAF where the the geese function from package geepack is used.

Usage

geepack.lgst.int.batch.imputed(genfile,phenfile,pedfile,outfile,phen,
covars,cov.int,sub="N",col.names=T,sep.ped=",",sep.phe=",",sep.gen=",")

Arguments

genfile	a character string naming the genotype file for reading (see format requirement in details)
phenfile	a character string naming the phenotype file for reading (see format requirement in details)
pedfile	a character string naming the pedigree file for reading (see format requirement in details)
outfile	a character string naming the result file for writing
phen	a character string for a phenotype name in phenfile
covars	a character vector for covariates in phenfile
cov.int	a character string naming the covariate for interaction, the covariate has to be included in covars
sub	"N" (default) for no stratified analysis, and "Y" for requesting stratified analyses (only when cov.int is dichotomous)
col.names	a logical value indicating whether the output file should contain column names
sep.ped	the field separator character for pedigree file
sep.phe	the field separator character for phenotype file
sep.gen	the field separator character for genotype file

Details

Similar to the details for geepack.lgst.int.batch but here the SNP data contains imputed genotypes (allele dosages) that are continuous and range from 0 to 2.

Value

No value is returned. Instead, results are written to outfile. If stratified analyses are requested, the result file will include the following columns. Otherwise, cov_beta_snp_beta_int will be included instead of the results from stratified analyses, that is, beta_snp_cov0, se_snp_cov0, pval_snp_cov0, beta_snp_cov1, se_snp_cov1, and pval_snp_cov1.

phen	phenotype name
snp	SNP name
covar_int	the covariate for interaction
n	sample size used in analysis
AF	allele frequency of the coded allele
nd	the number of individuals in affected sample
AFd	allele frequency of the coded allele in affected sample
model	genetic model used in analysis, additive model only
beta_snp	regression coefficient of SNP covariate
se_snp	standard error of beta_snp
pval_snp	p-value of testing beta_snp not equal to zero
beta_snp_cov0	regression coefficient of SNP covariate in stratified analysis using the subset where cov.int level is 0
se_snp_cov0	standard error of beta_snp_cov0
pval_snp_cov0	p-value of testing beta_snp_cov0 not equal to zero
beta_snp_cov1	regression coefficient of SNP covariate in stratified analysis using the subset where cov.int level is 1
se_snp_cov1	standard error of beta_snp_cov1
pval_snp_cov1	p-value of testing beta_snp_cov1 not equal to zero
beta_int	regression coefficient of the interaction term
se_int	standard error of beta_int
pval_int	p-value of testing beta_int not equal to zero
remark	warning or additional information for the analysis, 'not converged' indicates the GEE analysis did not converge; 'logistic reg' indicates GEE model is replaced by logistic regression; 'exp count<5' indicates any expected count is less than 5 in phenotype-genotype table; 'not converged and exp count<5', 'logistic reg & exp count<5' are noted similarly; 'collinearity' indicates collinearity exists between SNP and some covariates

Author(s)

Qiong Yang <[e-mail]> and Ming-Huei Chen <[e-mail]>

Examples

## Not run: 
geepack.lgst.int.batch.imputed(phenfile="simphen.csv",genfile="simgen.csv",
pedfile="simped.csv",phen="CVD",outfile="simout.csv",covars=c("sex","age"),cov.int="sex",
sub="Y",sep.ped=",",sep.phe=",",sep.gen=",")

## End(Not run)

GWAF documentation built on May 2, 2019, 2:47 p.m.